This study employs a super-efficiency Slacks-Based Measure (SBM) model combined with the Global Malmquist-Luenberger (GML) index to measure the Green Total Factor Productivity (GTFP) of the mining industry, based on an ecological-technology-economic co-evolution perspective. It comprehensively evaluates the green development level of Xinjiang's mining industrial cluster, a representative ecologically fragile region. Results indicate that Xinjiang's mining GTFP lags behind the national average, with insufficient technological innovation capability remaining a key constraint. Quantitative analysis using the location entropy method reveals that Xinjiang's mineral resource industry exhibits characteristics of "high agglomeration, low green efficiency, and fragmented industrial chains," demonstrating a state of cluster "pseudo-prosperity." Empirical analysis via a Vector Autoregression (VAR) model elucidates the dynamic relationship between agglomeration degree, green development, and economic performance. Findings demonstrate that green benefits significantly influence mining cluster agglomeration, and the synergy between green benefits and industrial agglomeration constitutes the core driver for sustainable economic development, forming a positive feedback loop of "green technology → industrial agglomeration → economic efficiency enhancement." The study proposes establishing a "quadruple-helix" green development system centered on "ecological value-added, technology enablement, network synergy, and structural optimization" to provide countermeasures for the green, high-quality development of mining clusters.